Preprint reveals a STAMP framework for safety in autonomous agents, suggesting improved accountability and compliance.
Autonomous agent systems are increasingly deployed where consequential actions (API calls, data access,transactions) matter for safety, privacy, and compliance. Much of the prevailing stack is observational oradvisory: prompts, filters, checkpoints, and logs that do not always sit on the causal path to side effects.This paper connects Nancy Leveson’s STAMP/STPA tradition—safety as control of a controlledprocess, with feedback and an explicit process model—to Agent Responsibility Engineering (ARE)—adiscipline with public orientation at srex-dev/AgentResponsibilityEngineering, evaluated in this preprintagainst a privately held reference implementation (this manuscript describes control structure andsafety case, not a turnkey public product drop).We present a bounded STAMP/STPA closure safety case at a defined execution boundary, nota proof of “safe AI” in the large. Closure means: every hazard in scope in the working STPA packageis mitigated, accepted with documented residual risk, or assumption-bounded, as recorded inSTPA_RESOLUTION.md (same file appears in the public mirror under research/stpa/ and in a private monolith clone under research/stpa/). The case is supported by traceability (losses, hazards, unsafe controlactions, constraints), component tests (Rust and Go services on the golden path), an interposition audit, and a frozen reviewer evidence bundle (commit-attested). A TLA+ specification skeleton statesordering obligations; it is not a machine-checked proof.We do not claim universal fail-closed behavior in every subsystem, production validation in a named sector,or bidirectional formal proof of every narrative mapping in the broader ARE research program. We do claim:(1) a STAMP-aligned control reading of the governed path; (2) causal interposition (policy coprocessor→ pre-execution validation → receipt binding → executor); (3) fail-closed semantics for a permit verdictwhen the immutable Ledger write fails at the coprocessor (permit cannot leave without durable evidence—Deny with documented reason); (4) explicit residual risk and out-of-scope surfaces (deployment routing,strata composition, distributed lag, human escalation).
No takes yet. Share an insight, caveat, or question.
Jonathan Kershaw (2026) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: